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Asymptotic normality of multi-dimension quasi maximum likelihood estimate in generalized linear models with adaptive design

Authors:	Li?Guoliang Gao?Qibing Email author" target="_blank">Liu?Luqin Email author

Institution:	(1) School of Mathematics and Statistics, Wuhan University, 430072 Wuhan, Hubei, China;(2) Department of Statistics and Finance, University of Science and Technology of China, 230026 Hefei, Anhui, China

Abstract:	We study the quasi likelihood equation in Generalized Linear Models (GLM) with adaptive design $\sum\limits_{i = 1}^n {x_i } (y_i - h(x'_i \beta )) = 0$ ,where y_i, is aq-vector, andx _i, is ap×q random matrix. Under some assumptions, it is shown that the Quasi-Likelihood equation for the GLM has a solution which is asymptotic normal. Foundation item: Supported by the National Natural Science Foundation of China (10371092) Biography: LI Guoliang(1978-), male, Ph.D candidate, research direction: linear models, generalized linear models, and large sample method of statistics

Keywords:	generalized linear model(GLM) adaptive design the quasi likelihood estimate asymptotic normality
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